[Eeglablist] Setting epoch limits

[Makoto Miyakoshi]

Dear Elisa,

There is timewarp option in newtimef() function. With this option turned
on, you can stretch or shrink single trials with variable length into
normalized length. This is only possible after time-frequency transform
(otherwise you'll change frequencies as you stretch or shrink the lengths).
However, here is my warning; using time-warp option may be tricky. You want
to spend a good length of time to try it out carefully with exploratory
mind.

Makoto

On Mon, Jan 25, 2016 at 2:00 AM, Elisa Tatti <elisatatti at msn.com> wrote:

> Dear all,
> first of all, I want to thank all of you; I am learning so much about EEG
> analysis thank to this discussion list.
>
> I designed my first EEG experiment to study changes in
> electrophysiological activity during a reasoning task. In my paradigm,
> subjects had up to 15'' to give an answer, which triggered the EEG as the
> subject pressed the keyboard. One second lasting fixation cross was shown
> before the next trial.
> I want to epoch the data on the onset of the matrix to run time-frequency
> analysis on the trials with a correct response.
> Here is my doubt: given that there is great variability in the  mean
> response times between subjects (min 3''-max 10''), how should I select the
> proper epoch limits for all the subjects?
>
> My concern is that, if I select a large epoch limit to analyze the
> processing of the slowest subject, I am variably including the next trial
> (which is a different condition) of the fastest subjects. Nevertheless, if
> I set the epoch limit to the fastest RT, I am going to limit the analysis
> to the processing of the fastest subjects (which may be the smartest as
> well).
> I searched research articles that investigated similar cognitive functions
> (e.g. reasoning, insight) but I did not find any answer to my doubt.
>
> I am thinking about extracting epochs of the same length (-1 8'') by
> writing a script that merges the fastest epochs with the resting EEG
> recording  (trial by trial for every subject). What do you think about it?
>
> I really appreciate any help you can provide.
>
> Best,
>
> Elisa
>
>
>
>
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-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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